Cyclops uses machine learning to improve analytics for offline businesses
Brick and mortar shopping has been around a lot longer than online shopping, but it’s much harder to analyze physical actions compared to tracking digital interactions. We wanted to convey that message, and then show how Cyclops uses machine learning to integrate with store cameras to provide detailed customer analytics. But before any of that, we needed to grab people’s attention.
Rather than jumping directly into product details and benefits, we instead created a metaphor to hook the video viewer in. In the second shot, everything is blurry to represent the difficulty traditional retail stores have in recognizing buying patterns. The hand wipes it clean, instantly making an association in the viewers’ minds that Cyclops makes understanding what’s going on inside your store instantly clearer. The best part about this is that the message is understood just with visuals. Before Cyclops, you only had a vague idea of customer habits within your business. With Cyclops, a whole new world of details opens up. The message of what Cyclops can do for a physical store is instantly communicated, making it easy to then share details of customer benefits to a receptive audience.
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
Animation production: Yans Media
Style: 2D motion graphics
Vertical(s) High Tech
Creative Direction: Tigran Movsisyan
Illustrations: Gayane Hakobian, Anet Hovhannisyan
Motion Graphics: Smbat Harutyunyan, David Bagdasaryan